ACDC Lab

Advanced Cross-media Data Computing Group

Cross-media Data Computing Β· Explore Intelligence, Connect the World

Focusing on social media & data mining, AI applications, multimodal learning and large models, we are dedicated to data-driven intelligent computing and applied innovation.

Jinpeng Chen

About the Group

GROUP INTRODUCTION

The ACDC group is led by Prof. Jinpeng Chen, Associate Professor and Doctoral Advisor at the School of Computer Science (National Model Software College), Beijing University of Posts and Telecommunications (BUPT), and Deputy Director of the Digital & Intelligent Transformation Department. His research interests include data mining & intelligent computing, AI & applications, and multimodal learning. He has led or participated in 40+ national, provincial/ministerial, and industry research projects, published 100+ papers at leading venues such as SIGIR, WWW, NeurIPS, ICML, AAAI, ACM MM, ACL, EMNLP, TKDE, and TMC, and holds 14 granted/pending patents.

He received the ICONIP 2022 Best Paper Award, the Zhou Jiongpan Outstanding Young Teacher Award, and the "Beijing Mobile" Teaching Innovation Award, among others. He serves on the CAAI Intelligent Service Technical Committee and the CIPS Social Media Processing & Language and Knowledge Computing Technical Committees, and as an early-career editorial board member of Big Data Mining and Analytics, executive committee member of Computer Science, and assistant editor of the Journal of Intelligent Systems.

πŸ‘₯

Welcome to the ACDC Family

Our research currently focuses on recommender systems / model lightweighting / autonomous driving. We welcome collaborators in related directions; interested students are invited to send your CV to jpchen [at] bupt [dot] edu [dot] cn.

Computing resources: the group maintains dedicated compute resources and also rents substantial AutoDL capacity for model training.

Research Directions

MAIN RESEARCH

01

Recommender Systems

Personalized recommendation over large-scale data, including retrieval, ranking, diversity, and explainability.

Learn more β†’
Recommender Systems
02

Multimodal Learning

Representation learning and fusion modeling of text, image, video, and audio for cross-modal understanding and generation.

Learn more β†’
Multimodal Learning
03

Multi-Agent Learning

Multi-agent collaboration and game theory, reinforcement learning and decision optimization for complex intelligent agent systems.

Learn more β†’
Multi-Agent Learning

JOIN US

Join ACDC and Create the Future Together

Work alongside talented peers, explore cutting-edge technology, solve real-world problems, and turn ideas into impact.